Shangkun Wang, H. Milton, Adam P. Generale, S. Kalidindi, George W. Woodruff, V. Roshan, Joseph H. Milton
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Space-filling designs are commonly used in computer experiments to fill the space of inputs so that the input-output relationship can be accurately estimated. However, in certain applications such as inverse design or feature-based modeling, the aim is to fill the response or feature space. In this article, we propose a new experimental design framework that aims to fill the space of the outputs (responses or features). The design is adaptive and model-free, and therefore is expected to be robust to different kinds of modeling choices and input-output relationships. Several examples are given to show the advantages of the proposed method over the traditional input space-filling designs.
期刊介绍:
Technometrics is a Journal of Statistics for the Physical, Chemical, and Engineering Sciences, and is published Quarterly by the American Society for Quality and the American Statistical Association.Since its inception in 1959, the mission of Technometrics has been to contribute to the development and use of statistical methods in the physical, chemical, and engineering sciences.